Using the output from Step #2, you will need to insert the intercepts and slopes for each class within each group (the control and treatment groups, in our case) into the LCA Outcome Probability Calculator. As is shown below, the top box represents the parameters for the control group and the bottom box represents the parameters for the treatment group. The cells highlighted in yellow represent those in which the user must enter information.
First, you will enter the intercept and slope estimates from the SAS output in Step #2 into the intercept and slope cells located in the spreadsheet. After you have inserted all of the intercept and slope estimates, next you will need to insert the marginal frequencies for the outcome (t2binge) in each treatment condition (control, treatment) from the SAS output in Step #3. For example, 703 adolescents in the control condition report “no” to binge drinking and therefore you will input this number into the cell labeled “N with outcome=0” in the top box where the control parameters are located. Once all of the intercepts, slopes and marginal frequencies are entered into the calculator for each class within each group, the calculator will automatically populate the probabilities listed in the far right column (cells highlighted in blue are probabilities for the control group and cells highlighted in orange are probabilities for the treatment group). These probabilities will sum to one within each group.
The following is one way to display the results obtained above from the LCA Outcome Probability Calculator. This graph will automatically populate based on the parameters entered into the calculator. In our case, this presents the proportion of treatment and control participants in each risk subgroup reporting binge drinking at Grade 9.
Harris, K. M., Halpern, C. T., Whitsel, E., Hussey, J., Tabor, J., Entzel, P., & J.R. Udry. (2009). The National Longitudinal Study of Adolescent Health: Research design [WWW document]. Retrieved from http://www.cpc.unc.edu/projects/addhealth/design
Lanza, S. T. & Rhoades, B. L. (2011). Latent class analysis: An alternative perspective on subgroup analysis in prevention and treatment. Prevention Science, 14(2), 157-168. doi:10.1007/s11121-011-0201-1 PMCID: PMC3173585 View abstract
Lanza, S. T., Rhoades, B. L., Nix, R., & Greenberg, M. T. (2010). Modeling the interplay of multilevel risk factors for future academic and behavior problems: A person-centered approach. Development and Psychopathology, 22, 313-335. PMCID: PMC3005302 View article